Relative location prediction in CT scan images using convolutional neural networks.

Journal: Computer methods and programs in biomedicine
Published Date: Mar 28, 2018

Abstract

BACKGROUND AND OBJECTIVE: Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and speed of these methods cannot meet the requirement of medical scenario. In this paper, we propose a regression model based on one-dimensional convolutional neural networks (CNN) to determine the relative location of a CT scan image both quickly and precisely.

Authors

  • Jiajia Guo
    Center for Biomedical Imaging, University of Science and Technology of China, Hefei, Anhui, China.
  • Hongwei Du
    Center for Biomedical Imaging, University of Science and Technology of China, Hefei, Anhui, China. Electronic address: duhw@ustc.edu.cn.
  • Jianyue Zhu
    National Mobile Communications Research Lab, School of Information Science and Engineering, Southeast University, Nanjing, China.
  • Ting Yan
    Center for Biomedical Imaging, University of Science and Technology of China, Hefei, Anhui, China.
  • Bensheng Qiu
    Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui 230027, China.

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